class_docstr: The containing dialog and controller for the embedding
  and the image viewer that together make up an analysis
  (i.e. a user selection at an hSNE scale). It also
  iterates over the embedding once the analysis is created
  and this is dynamically displayed in the embedding gui.
docstr: Selection indexes in this analysis are converted to original
  data point indexes
docstr_tok: ["Selection","indexes","in","this","analysis","are","converted","to","original","data","point","indexes"]
code: def data_index_from_selection(self, sel_indexes):
      """Selection indexes in this analysis are converted to original
      data point indexes"""
      data_indexes = []
      # Translate the landmark indexes to the original data indexes
      for i in sel_indexes:
          data_indexes.append(self.analysis.landmark_orig_indexes[i])
      return data_indexes
  
imports: import time
  import numpy
  from PyQt5 import QtWidgets
  from EmbeddingGui import EmbeddingViewer
  from ModelGui import DemoType
  from CompositeImageViewer import CompositeImageViewer
  from HyperspectralImageViewer import HyperspectralImageViewer
  from MetaDataViewer import MetaDataViewer
label_desc: Use image node_id 6 for calling the AnalysisController obj's underlying member method code with example usage: obj.data_index_from_selection(sel_indexes) and returns: data_indexes